在2013的最后一天,看了@fenng大 的小道消息,我也心血来潮写个技术终结,把过去3年一个总结了吧。 题外话: 今年我终于是大四狗了,话说大学快结束了,学校的课一点都不会,不说了,说多了字字句句都是泪
在2013的最后一天,看了@fenng大 的小道消息,我也心血来潮写个技术终结,把过去3年一个总结了吧。题外话:
今年我终于是大四狗了,话说大学快结束了,学校的课一点都不会,不说了,说多了字字句句都是泪啊。。。。
1.从大一到大三把 oracle 的体系结构 搞了一遍,虽不能说纵览全局,但也勉强可以称得上熟悉了。
2.2013这年,大多时间都花在10g的rac crs,11g的rac grid,对这两个版本有了一些基本认识,之前看了10g rac 的sg,11g的sg,看了后一团迷糊,很多概念都很迷糊。这一块2014年还得继续搞,对了差点忘了 dg,ogg 了,dg在2013年搞的并不多,就弄过3个项目,感觉不是特别爽,还得继续弄。
3.performance tuning 这块今年也不咋地,尤其是sql tuning ,看了黄玮前辈的sql 高性能引擎。后面的内容基本看不懂,一直在想看懂这些内容对工作有什么好处,目前还么想通。
4.shell, pythong等还是很欠缺,一直没决心去完整学习下。很是惭愧啊!
5.linux unix os这块也没有好好去搞下,也是一些三脚猫,又欠了一笔账,个人还是非常看好linux的。
6、另外就是java了,这个主要是为了自己以后it路可以走的更宽而作准备的,按目前的形式来看,x86以后是大趋势,这也就意味着自动化运维是必须要面对的挑战。
7.除了一些技术的书,貌似今年也没看多少,人文类的书还是要多多看点,毕竟生活才是第一位。
2013的总结草草几笔,算是终结了这几年。。。诶。。。。看来只能在2014年爆发了,出来混的,总是要还的,2013 欠的债,就只能子啊2014年不上了,在毕业前,交出一份让自己满意的答卷。
2014规划如下,(这个是现在想到的,后续还得继续补充啊)
1. 10、11g rac,crs的安装,体系结构,troubleshooting,performance tuning,结合rac internal 的几个reference 深入学习下,然后总结出自己的几个文档。
2.10、11g单实例的体系结构还需要深入理解下,以concepts 为主,还需再各读一遍 。
3.sql tuning也要开始要花点心思了,争取可以做一些基本的sql 调优。
4.os linux,and unix(aix hp-ux) 也开始要好好系统学习下了。
5.shell 等脚本语言也要会自己写了,这可是必须的技能。
6.java,python 这两个是为了未来的职业生涯做准备。
7.业余时间不要在浪费了,不再去逛qq空间类的(必须禁用),微博也要有节制,多去info 之类的网站学习下前辈们的思想,和了解最新的前言技术,行业技术趋势,开阔自己的眼界 ,增长自己的知识面,其他的还要去看那个曼昆的经济学原理,不然白买了,对不起最初买书的目的。
8.电脑了资料太多了,这个得好好整理下了。
9.目前能想到的就这些了,想到了在补充下。。。。
感谢2013年里那些帮助过我 的各位前辈们,以及我的几位师傅。
最后,预祝自己在2014年更上十层楼!啦啦啦啦啦!

Stored procedures are precompiled SQL statements in MySQL for improving performance and simplifying complex operations. 1. Improve performance: After the first compilation, subsequent calls do not need to be recompiled. 2. Improve security: Restrict data table access through permission control. 3. Simplify complex operations: combine multiple SQL statements to simplify application layer logic.

The working principle of MySQL query cache is to store the results of SELECT query, and when the same query is executed again, the cached results are directly returned. 1) Query cache improves database reading performance and finds cached results through hash values. 2) Simple configuration, set query_cache_type and query_cache_size in MySQL configuration file. 3) Use the SQL_NO_CACHE keyword to disable the cache of specific queries. 4) In high-frequency update environments, query cache may cause performance bottlenecks and needs to be optimized for use through monitoring and adjustment of parameters.

The reasons why MySQL is widely used in various projects include: 1. High performance and scalability, supporting multiple storage engines; 2. Easy to use and maintain, simple configuration and rich tools; 3. Rich ecosystem, attracting a large number of community and third-party tool support; 4. Cross-platform support, suitable for multiple operating systems.

The steps for upgrading MySQL database include: 1. Backup the database, 2. Stop the current MySQL service, 3. Install the new version of MySQL, 4. Start the new version of MySQL service, 5. Recover the database. Compatibility issues are required during the upgrade process, and advanced tools such as PerconaToolkit can be used for testing and optimization.

MySQL backup policies include logical backup, physical backup, incremental backup, replication-based backup, and cloud backup. 1. Logical backup uses mysqldump to export database structure and data, which is suitable for small databases and version migrations. 2. Physical backups are fast and comprehensive by copying data files, but require database consistency. 3. Incremental backup uses binary logging to record changes, which is suitable for large databases. 4. Replication-based backup reduces the impact on the production system by backing up from the server. 5. Cloud backups such as AmazonRDS provide automation solutions, but costs and control need to be considered. When selecting a policy, database size, downtime tolerance, recovery time, and recovery point goals should be considered.

MySQLclusteringenhancesdatabaserobustnessandscalabilitybydistributingdataacrossmultiplenodes.ItusestheNDBenginefordatareplicationandfaulttolerance,ensuringhighavailability.Setupinvolvesconfiguringmanagement,data,andSQLnodes,withcarefulmonitoringandpe

Optimizing database schema design in MySQL can improve performance through the following steps: 1. Index optimization: Create indexes on common query columns, balancing the overhead of query and inserting updates. 2. Table structure optimization: Reduce data redundancy through normalization or anti-normalization and improve access efficiency. 3. Data type selection: Use appropriate data types, such as INT instead of VARCHAR, to reduce storage space. 4. Partitioning and sub-table: For large data volumes, use partitioning and sub-table to disperse data to improve query and maintenance efficiency.

TooptimizeMySQLperformance,followthesesteps:1)Implementproperindexingtospeedupqueries,2)UseEXPLAINtoanalyzeandoptimizequeryperformance,3)Adjustserverconfigurationsettingslikeinnodb_buffer_pool_sizeandmax_connections,4)Usepartitioningforlargetablestoi


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